Organ-Specific Expression of IL-1 Receptor Results in Severe Liver Injury in Type I Interferon Receptor Deficient Mice

Upon treatment with polyinosinic:polycytidylic acid [poly(I:C)], an artificial double-stranded RNA, type I interferon receptor-deficient (IFNAR−/−) mice develop severe liver injury seen by enhanced alanine aminotransferase (ALT) activity in the serum that is not observed in their wildtype (WT) counterparts. Recently, we showed that liver injury is mediated by an imbalanced expression of interleukin (IL)-1β and its receptor antagonist (IL1-RA) in the absence of type I IFN. Here we show that despite comparable expression levels of IL-1β in livers and spleens, spleens of poly(I:C)-treated IFNAR−/− mice show no signs of injury. In vitro analyses of hepatocytes and splenocytes revealed that poly(I:C) had no direct toxic effect on hepatocytes. Furthermore, expression levels of cytokines involved in other models for liver damage or protection such as interferon (IFN)-γ, transforming growth factor (TGF)-β, IL-6, IL-10, IL-17, and IL-22 were comparable for both organs in WT and IFNAR−/− mice upon treatment. Moreover, flow cytometric analyses showed that the composition of different immune cells in livers and spleens were not altered upon injection of poly(I:C). Finally, we demonstrated that the receptor binding IL-1β, IL1R1, is specifically expressed in livers but not spleens of WT and IFNAR−/− mice. Accordingly, mice double-deficient for IFNAR and IL1R1 developed no liver injury upon poly(I:C) treatment and showed ALT activities comparable to those of WT mice. Collectively, liver injury is mediated by the organ-specific expression of IL1R1 in the liver

Transformando enseñanzas presenciales en semipresenciales: un ejemplo, la especialidad de Formación y Orientación Laboral en el Máster en Formación del Profesorado. Protocolo de actuación, evaluación y nuevos diseños para la docencia universitaria

Fac. de Ciencias Políticas y SociologíaFALSEsubmitte

Representative Sinusoids for Hepatic Four-Scale Pharmacokinetics Simulations.

The mammalian liver plays a key role for metabolism and detoxification of xenobiotics in the body. The corresponding biochemical processes are typically subject to spatial variations at different length scales. Zonal enzyme expression along sinusoids leads to zonated metabolization already in the healthy state. Pathological states of the liver may involve liver cells affected in a zonated manner or heterogeneously across the whole organ. This spatial heterogeneity, however, cannot be described by most computational models which usually consider the liver as a homogeneous, well-stirred organ. The goal of this article is to present a methodology to extend whole-body pharmacokinetics models by a detailed liver model, combining different modeling approaches from the literature. This approach results in an integrated four-scale model, from single cells via sinusoids and the organ to the whole organism, capable of mechanistically representing metabolization inhomogeneity in livers at different spatial scales. Moreover, the model shows circulatory mixing effects due to a delayed recirculation through the surrounding organism. To show that this approach is generally applicable for different physiological processes, we show three applications as proofs of concept, covering a range of species, compounds, and diseased states: clearance of midazolam in steatotic human livers, clearance of caffeine in mouse livers regenerating from necrosis, and a parameter study on the impact of different cell entities on insulin uptake in mouse livers. The examples illustrate how variations only discernible at the local scale influence substance distribution in the plasma at the whole-body level. In particular, our results show that simultaneously considering variations at all relevant spatial scales may be necessary to understand their impact on observations at the organism scale

Computational Performance.

<p>For our applications with different numbers # rs of representative sinusoids, the table lists the computational performance as a multiple of real-time performance (larger is faster) as well as the memory needed for the respective simulation. For the insulin model, the number refers to one of the 4096 simulations run as part of the parameter study.</p

Steatosis Inhomogeneity.

<p>The <i>left</i> image shows a histological image of a human liver with selected portal fields and central veins marked as ⊙ and ⊗, respectively. The <i>right</i> image shows a histological whole-slide scan of a steatotic mouse liver and a zoom to one lobe. Macrovesicular steatosis, i.e., lipid accumulations of diameter larger than hepatocyte nuclei, was quantified in all cases using an image analysis method based on [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133653#pone.0133653.ref014" target="_blank">14</a>] and visualized as an overlay to the histological images, using a color map from violet to yellow indicating low to high steatosis. The left example shows a pericentrally zonated state of steatosis. The right example shows both organ-scale and lobe-scale heterogeneity in the steatosis distribution in addition to a periportal zonation not clearly visible at this magnification. The human image data is by Serene Lee and Wolfgang Thasler, Department of General, Visceral, Transplantation, Vascular and Thoracic Surgery Ludwig Maximilians University Munich Medical Center; the mouse image data is by Uta Dahmen, Department of General, Visceral and Vascular Surgery, University Hospital Jena; the analysis overlay was provided by André Homeyer, Fraunhofer MEVIS, Bremen.</p

Necrosis and Regeneration.

<p>The plot shows how the spatial extent of the necrotic region evolves according to our model of the effect of CCl₄ intoxication along a representative sinusoid of a mouse liver. The representative hepatocytes are separated by vertical black lines in this plot, A color range from white to red indicates zero to full necrotic damage of the respective representative hepatocyte. Necrosis develops during the first day, until a maximally necrotic state is attained. Subsequent regeneration starting on the second day leads to a shrinkage of the necrotic region until the end of day 7.</p

Influence of the Body Delay.

<p>For an intravenous bolus injection in our human whole-body model with a liver described by a single representative sinusoid, the plot shows the simulated midazolam concentration in the blood plasma at the liver inflow. Setting the temporal delay of the recirculation to zero (dashed line) shows that the delay in the model is indispensable for a correct prediction of recurring peaks for a second and third pass, indicated by circled numbers in the plot.</p

Spatio-Temporal Midazolam Concentration Profiles.

<p>The surface plots show the spatio-temporal evolution of the midazolam concentrations in the blood plasma and the hepatocytes along representative sinusoids assuming an infusion of duration 5 seconds into the portal vein, comparing the healthy reference case with three different steatotic cases with the same total amount of lipid accumulation. While the height in the graph covers the total concentration ranges, the color highlights differences in a lower range of concentrations, emphasizing the differences between the four cases. In addition, the steatosis patterns along the sinusoids are shown below the cellular concentrations. Differences in the transit time of the peak are due to different extent of storage and release of the midazolam due to the steatotic lipid accumulations. This should not be mistaken for the blood flow transit time, which is 13.6 s for all four cases and thus much shorter than the peak transit time.</p

Insulin Model.

<p>The <i>top left</i> plots show two datasets for evaluating the amount of insulin binding to individual cells by flow cytometry (FACS). The upper panel exemplarily shows the raw measurements five minutes after stimulation with 100 nM, the lower panel for 1000 nM. Independent of time and insulin dose, a bimodal distribution was observed indicating two entities of hepatocytes. Two Gaussian distributions were fitted to the logarithmic intensity histograms to analyze the time and dose dependency of the average insulin binding within both entities. The <i>top right</i> sketch shows the structure of the model for cellular insulin binding, internalization and extraction processes described by <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133653#pone.0133653.e045" target="_blank">Eq 21</a> including the parameters given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133653#pone.0133653.e046" target="_blank">Eq 22</a>. This model could explain the dynamics for both entities of hepatocytes as seen in the <i>bottom</i> plot showing the model fit of time-dependent average insulin binding of both entities for three different doses. The experimentally observed data for low-binding and high-binding hepatocytes is shown as ‘+’ and ‘×’, respectively. Model predictions for these cases are solid and dashed lines, respectively. The shaded error bands correspond to the estimated error in the data points.</p

Sketch for the 1D Representation of Sinusoids.

<p>The volume rendering in the <i>middle</i> illustrates our assumption of multiple periportally starting sinusoids contributing to a thicker pericentrally terminating sinusoid. The width of the interstitial and cellular layer is assumed to remain constant along the sinusoid. The sinusoidal cross-section sketches on the <i>left</i> and <i>right</i> show that this also has an effect on the respective surface areas, which has an influence on the respective effective permeabilities.</p